The U.S. EPA (Suppl Guidance for Conducting Health Risk Assessment of Chemical Mixtures, 2000) suggests that when toxicity data are not available for a mixture of concern, the risk assessment of the mixture can be based on data for a surrogate mixture which is considered "sufficiently similar" in terms of chemical composition and component proportions, and when available, considerations of similar biological disposition and toxicity. The objective of this research is to develop methodology to define sufficient similarity in dose-responsiveness for mixtures of many chemicals containing the same components, but whose component ratios vary. The method assumes that dose-response data on a fixed-ratio mixture are available. Statistical equivalence testing logic will be applied to define boundary ratios for mixtures with mean, dose-response relationships sufficiently similar to an observed mixture, based on a specified biologically meaningful region of insensitivity as defined by the investigator using expert judgment. Once the methodology is further developed as described herein, simulation studies will be conducted to elucidate the properties of the approach. The simulation study will be based on data from at least three dose-response curves of mixtures of chemicals including: (1) a mixture of 11 pesticides (pyrethroids) and the effect on neurotoxicity;(2) a mixture of 18 polyhalogenated aromatic hydrocarbons in a fixed ratio based on evaluation offish tissue, breast rnilk and other sources of human exposure and the effect on thyroid disruption;(3) a mixture of 5 organophosphorous pesticides in a relevant ratio based on dietary exposures and the effect on neurotoxicity. The result of this research will impact public health by adding new approaches to the risk assessment of chemical mixtures. In particular, all possible environmentally/industrially relevant chemical mixtures to which humans are exposed cannot each be evaluated for risk. The funded project will further develop/characterize a method of determining sufficient similarity in dose-responsiveness for mixtures with many components.